This project is a modular, computationally-distributed multi-robot cyberphysical system (CPS) for assisting young developmentally-delayed children in learning to walk. The multi-robot CPS is designed to function in the same way as an adult assisting a child in learning to walk (addressing the research target area of a science of CPS by introducing developmental rehabilitation robotics). It addresses the research target area of new CPS technology by introducing a multi-robot system: 1) a multi-cable scaffold robot that continuously modulates the stabilization of medio-lateral and anterior-posterior sway, and 2) a soft, wearable, exosuit robot with embedded sensing and actuation, which assists with stance push off and swing flexion. The objective is to build a prototype multi-robot CPS and perform tests with human subjects to evaluate the CPS functionality, safety, and interoperability (addressing the research target area of engineering CPS). Longitudinal tests of typically developing and developmentally delayed children learning to walk with or without assistance of the multi-robot CPS are conducted in a motion capture laboratory. Body center of mass behavior as well as gait parameters of walking are measured as the two robots work together to assist the child in maintaining balance and propelling the body forward with each step. This exosuit/scaffolding multi-robot technology will advance knowledge within engineering with bio-inspired soft components, including miniature pneumatic artificial muscle actuators with embedded sensors that enable the control of the muscles in real time. The bio-inspired architecture and material components of the exosuit will make possible a new generation of ?smart fabric? that acts in concert with the body for efficient energy use. The exosuit is part of a larger modular design that makes it possible to couple it to additional assistive robots via a modular communications network. Together, the exosuit, scaffold robot, and wireless communications network for modular CPS, will advance knowledge for the engineering of other CPS that require high levels of interoperability and safety, such as medical CPS. The multi-robot CPS is designed for children who are developmentally delayed as a result of early brain injury. The long term consequences of early brain injury, e.g., in children born prematurely, constitute a major health problem and a significant emotional and financial burden for families and society. The use of a multi-robot cyberphysical system as part of a rehabilitation program may be able to harness the potential of the nervous system for plasticity, the ability to re-organize its structure, function, and connections. The focus is on young children with a history of early brain injury due to prematurity. However, this new cyberphysical system will have a much broader impact in restoring function throughout the life span. Neuroplasticity is not just an immediate response to injury, but occurs throughout the developmental period, providing an opportunity to promote repair and re-education, and restore function. A key to this broad application is the developmentally-motivated, modular structure and interoperability of the exosuit.

The objective of this research is to develop a comprehensive theoretical and experimental cyber-physical framework to enable intelligent human-environment interaction capabilities by a synergistic combination of computer vision and robotics. Specifically, the approach is applied to examine individualized remote rehabilitation with an intelligent, articulated, and adjustable lower limb orthotic brace to manage Knee Osteoarthritis, where a visual-sensing/dynamical-systems perspective is adopted to: (1) track and record patient/device interactions with internet-enabled commercial-off-the-shelf computer-vision-devices; (2) abstract the interactions into parametric and composable low-dimensional manifold representations; (3) link to quantitative biomechanical assessment of the individual patients; (4) facilitate development of individualized user models and exercise regimen; and (5) aid the progressive parametric refinement of exercises and adjustment of bracing devices. This research and its results will enable us to understand underlying human neuro-musculo-skeletal and locomotion principles by merging notions of quantitative data acquisition, and lower-order modeling coupled with individualized feedback. Beyond efficient representation, the quantitative visual models offer the potential to capture fundamental underlying physical, physiological, and behavioral mechanisms grounded on biomechanical assessments, and thereby afford insights into the generative hypotheses of human actions. Knee osteoarthritis is an important public health issue, because of high costs associated with treatments. The ability to leverage a quantitative paradigm, both in terms of diagnosis and prescription, to improve mobility and reduce pain in patients would be a significant benefit. Moreover, the home-based rehabilitation setting offers not only immense flexibility, but also access to a significantly greater portion of the patient population. The project is also integrated with extensive educational and outreach activities to serve a variety of communities.

This project develops the foundations of modeling, synthesis and development of verified medical device software and systems, from verified closed-loop models of the device and organ(s). The effort spans both implantable medical devices such as cardiac pacemakers and physiological control systems such as drug infusion pumps that have multiple networked medical systems. In both cases, the devices are physically connected to the body and exert direct control over the physiology and safety of the patient-in-the-loop. The goal is to ensure the device will never drive the patient into an unsafe state, while providing effective therapy. The contributions of are in three areas: closed-loop patient-device modeling; quantitative verification for optimized patient-specific devices; platforms for life-critical systems. Integrated modeling methodologies are developed to produce both the functional physiological signals, for clinically relevant testing with a medical device, and also generate the formal timing of device-patient interaction for formal verification. Starting with the problem of verifying the safety and correctness of medical device software, probabilistic patient models based on physiological data are then used to develop quantitative verification techniques to maintain the therapy?s efficacy on the patient and operational efficiency of the device. To facilitate participation of the CPS community, the Food and Drug Administration (FDA), physicians and manufacturers, open source libraries of device/patient models, software tools for verification and model translation and hardware platforms for testing with real medical devices are developed. The closed-loop design and verification techniques for medical device software and patients, developed here, have direct potential benefits on human health, and the quality and cost of medical care. Design of bug-free and safe medical device software is challenging, especially in complex implantable devices that control and actuate organs who's response is not fully understood. Safety recalls of pacemakers and implantable ?cardioverter? defibrillators between 1990 and 2000 affected over 600,000 devices. Of these, 200,000 or 41%, were due to firmware issues (i.e. software) that continue to increase in frequency. There is currently no formal methodology or open experimental platform to test and verify the correct operation of medical device software within the closed-loop context of the patient. If successful, this project has potential to not only increase the safety of such devices, but also to accelerate the development and certification process. The latter could reduce costs, and shorten the time to market for new devices. The project also has an extensive education and outreach component, including curriculum development in medical cyber-physical systems, involvement of undergraduate and graduate students in research, and cooperation with hospitals, makers of medical devices, and the FDA. The cross-cutting nature of the project brings together communities involving clinical physicians, electrical engineers, computer scientists and regulators of health care safety.

The objective of this research is to develop algorithms and software for treatment planning in intensity modulated radiation therapy under assumption of tumor and healthy organs motion. The current approach to addressing tumor motion in radiation therapy is to treat it as a problem and not as a therapeutic opportunity. However, it is possible that during tumor and healthy organs motion the tumor is better exposed for treatment, allowing for the prescribed dose treatment of the tumor (target) while reducing the exposure of healthy organs to radiation. The approach is to treat tumor and healthy organs motion as an opportunity to improve the treatment outcome, rather than as an obstacle that needs to be overcome. Intellectual Merit: The leading intellectual merit of this proposal is to develop treatment planning and delivery algorithms for motion-optimized intensity modulated radiation therapy that exploit differential organ motion to provide a dose distribution that surpasses the static case. This work will show that the proposed motion-optimized IMRT treatment planning paradigm provides superior dose distributions when compared to current state-of-the art motion management protocols. Broader Impact: Successful completion of the project will mark a major step for clinical applications of intensity modulated radiation therapy and will help to improve the quality of life of many cancer patients. The results could be integrated within existing devices and could be used for training of students and practitioners. The visualization software for dose accumulation could be used to train medical students in radiation therapy treatment planning.

This project aims to achieve key technology, infrastructure, and regulatory science advances for next generation medical systems based on the concept of medical application platforms (MAPs). A MAP is a safety/security-critical real-time computing platform for: (a) integrating heterogeneous devices and medical IT systems, (b) hosting application programs ("apps") that provide medical utility through the ability to both acquire information and update/control integrated devices, IT systems, and displays. The project will develop formal architectural and behavioral specification languages for defining MAPs, with a focus on techniques that enable compositional reasoning about MAP component interoperability and safety. These formal languages will include an extensible property language to enable the specification of real-time, quality-of-service, and attributes specific to medical contexts that can be leveraged by code generation, testing, and verification tools. The project will work closely with a synergistic team of clinicians, device industry partners, regulators, and medical device interoperability and safety standard organizations to develop an open source MAP innovation platform to enable key stakeholders within the nation's health care ecosphere to identify, prototype, and evaluate solutions to key technology and regulatory challenges that must be overcome to develop a commodity market of regulated MAP components. Because MAPs provide pre-built certified infrastructure and building blocks for rapidly developing multi-device medical applications, this research has the potential to usher in a new paradigm of medical system that significantly increases the pace of innovation, lowers development costs, enables new functionality by aggregating multiple devices into a system of systems, and achieves greater system safety.

This project's objective is to enable assertion-driven development and debugging of cyber-physical systems (CPS), in which required conditions are formalized as part of the design. In contrast with traditional uses of assertions in software engineering, CPS demand a tight coupling of the cyber with the physical, including in system validation. This project uses mathematical models of key physical attributes to guide creation of assertions, to identify inconsistent or infeasible assertions, and to localize potential causes for CPS failures. The goal is to produce methods and tools that use physical models to guide assertion-based verification of cyber-physical systems. An assertion language is being developed that is founded in mathematical logic while providing the familiarity of commonly used programming languages. This foundation enables new automated debugging techniques for CPS. By leveraging models that encode laws of physics and an automated decision procedure, the techniques being developed help identify causes of CPS failures by distinguishing inconsistent or infeasible physical states from valid ones. This model-based approach incorporates means to assess these physical states using both probabilistic and non-probabilistic measures. Two safety-critical applications guide the research and demonstrate the impact on the development of CPS: coordinated control of autonomous vehicles and monitoring and control of left-ventricular assist devices (LVADs). The focus on these safety-critical applications are motivational for recruiting and educating engineering students who have high expectations for how their lives should be enabled by computing advances. Further, this research advances methods needed to validate safe and effective CPS, promoting the public's confidence in their application to safety-critical systems.

This project aims to achieve key technology, infrastructure, and regulatory science advances for next generation medical systems based on the concept of medical application platforms (MAPs). A MAP is a safety/security-critical real-time computing platform for: (a) integrating heterogeneous devices and medical IT systems, (b) hosting application programs ("apps") that provide medical utility through the ability to both acquire information and update/control integrated devices, IT systems, and displays. The project will develop formal architectural and behavioral specification languages for defining MAPs, with a focus on techniques that enable compositional reasoning about MAP component interoperability and safety. These formal languages will include an extensible property language to enable the specification of real-time, quality-of-service, and attributes specific to medical contexts that can be leveraged by code generation, testing, and verification tools. The project will work closely with a synergistic team of clinicians, device industry partners, regulators, and medical device interoperability and safety standard organizations to develop an open source MAP innovation platform to enable key stakeholders within the nation's health care ecosphere to identify, prototype, and evaluate solutions to key technology and regulatory challenges that must be overcome to develop a commodity market of regulated MAP components. Because MAPs provide pre-built certified infrastructure and building blocks for rapidly developing multi-device medical applications, this research has the potential to usher in a new paradigm of medical system that significantly increases the pace of innovation, lowers development costs, enables new functionality by aggregating multiple devices into a system of systems, and achieves greater system safety.

This project, investigating formal languages as a general methodology for task transfer between distinct cyber-physical systems such as humans and robots, aims to expand the science of cyber physical systems by developing Motion Grammars that will enable task transfer between distinct systems. Formal languages are tools for encoding, describing and transferring structured knowledge. In natural language, the latter process is called communication. Similarly, we will develop a formal language through which arbitrary cyber-physical systems communicate tasks via structured actions. This investigation of Motion Grammars will contribute to the science of human cognition and the engineering of cyber-physical algorithms. By observing human activities during manipulation we will develop a novel class of hybrid control algorithms based on linguistic representations of task execution. These algorithms will broaden the capabilities of man-made systems and provide the infrastructure for motion transfer between humans, robots and broader systems in a generic context. Furthermore, the representation in a rigorous grammatical context will enable formal verification and validation in future work. Broader Impacts: The proposed research has direct applications to new solutions for manufacturing, medical treatments such as surgery, logistics and food processing. In turn, each of these areas has a significant impact on the efficiency and convenience of our daily lives. The PIs serve as coordinators of graduate/undergraduate programs and mentors to community schools. In order to guarantee that women and minorities have a significant role in the research, the PIs will annually invite K-12 students from Atlanta schools with primarily African American populations to the laboratories. One-day robot classes will be conducted that engage students in the excitement of hands-on science by interactively using lab equipment to transfer their manipulation skills to a robot arm.